CN112446603A - Cloud manufacturing system simulation method based on service agent - Google Patents
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Abstract
The invention discloses a cloud manufacturing system simulation method based on a service agent, and relates to the technical field of system modeling and simulation. The invention provides a method for simulating the behaviors of various elements in a cloud manufacturing environment by applying a multi-agent mode. Firstly, manufacturing resources are subjected to virtualization packaging to obtain a resource intelligent body packaging model, and the virtualized resources are packaged into manufacturing service to obtain a service intelligent body packaging model; on the basis, defining an interface and a communication mode; and finally, forming a multi-agent simulation framework facing the cloud manufacturing system. By the method, the characteristics of autonomy, diversity, randomness, intelligence and the like of the multi-agent can be effectively exerted, and the characteristics of resources and services in the cloud manufacturing environment are fully embodied. Compared with the traditional simulation method, more resources and service units can be simulated at the same time, and the simulation effect is more obvious particularly aiming at the characteristic that the resource and service time sequences are different.
Description
Technical Field
The invention relates to the technical field of system modeling and simulation, in particular to a cloud manufacturing system simulation method based on a service agent.
Background
With the rapid development of information technology and computer network technology, the traditional manufacturing model has not been able to meet the manufacturing requirements of modern production, and in order to respond to the rapid change of the market and improve the core competitiveness of enterprises, the industry and academic research have proposed a group of advanced manufacturing technologies or models, such as: manufacturing grid (MGrid), Global manufacturing (Global manufacturing), Virtual Manufacturing (VM), Agile Manufacturing (AM), and the like. Currently, research on networked manufacturing is mainly based on establishing an information sharing technology among enterprises, and by means of collaborative cooperation among the enterprises and integration and sharing of manufacturing resources, high-quality products capable of adapting to market changes are produced. Although the networked manufacturing has been greatly developed, there are certain problems in technology and operation mode, such as lack of centralized management and operation of services, failure to solve dynamic sharing and intelligent allocation of manufacturing resources and security in network communication and data transmission, and the like, which seriously hinder the popularization and application of networked manufacturing.
To solve these problems, the chinese institute of engineering, liber and academy, proposed a new model of networked manufacturing based on a Cloud computing service model, Cloud manufacturing (CMfg), in 1 month 2010. Cloud manufacturing technology is a new model of network-based, service-oriented manufacturing. The existing information-based manufacturing technology (information-based design, production, experiment, simulation and integration) and the emerging information technology (cloud computing, Internet of things, service computing, intelligent science, high-efficiency computing and the like) are fused and developed. Various manufacturing resources and manufacturing capabilities are virtualized and serviced to form a service cloud pool, unified and centralized management and management are carried out, and the manufacturing resources and the manufacturing capabilities are acquired at any time according to the requirements of customers through a network, so that various activities of the manufacturing whole life cycle are completed. With the development of cloud manufacturing concepts and related technologies, related cloud manufacturing simulation platforms are also continuously updated and iterated. The cloud manufacturing simulation platform is mainly used for simulating technologies such as modes, rules, algorithms and communication related to cloud manufacturing and verifying the related technologies. However, in the environment, whether resources, services or enterprise users are individuals with autonomy, independence and subjective knowledge of the environment. How to simulate the collaboration and interaction industries of these individuals is an important research content. The traditional single model can not satisfy the description of various individuals, and the real-time interaction effect is difficult to realize. Therefore, the invention provides a method for encapsulating resources and services by applying a multi-agent technology, and realizes an autonomous and independent agent to autonomously interact and cooperate with the surrounding environment and other individuals.
Disclosure of Invention
In view of the above, the invention provides a cloud manufacturing system simulation method based on a service agent, and the method of the invention integrates the characteristics of autonomy, independence, intelligence and the like of multiple agents, and improves the authenticity of simulation.
In order to achieve the purpose, the invention adopts the following technical scheme:
a cloud manufacturing system simulation method based on a service agent is characterized by comprising the following steps:
performing virtual packaging on manufacturing resources to obtain a resource intelligent body packaging model;
packaging the virtualized resources into manufacturing service to obtain a manufacturing service model;
packaging the manufacturing service again to obtain a service agent packaging model;
defining a communication interface and a communication mode on the basis of the resource agent encapsulation model and the service agent encapsulation model;
and establishing a cloud manufacturing simulation framework based on the multi-agent based on the resource agent packaging model and the service agent packaging model.
By adopting the scheme, the method has the following beneficial effects: resources, services and enterprise users in the cloud manufacturing environment have certain autonomy, independence and intelligence, and many behaviors are generated spontaneously and can adapt to changes of the surrounding environment. In order to solve the problem that the traditional modeling simulation mode is difficult to simulate the characteristics in the cloud manufacturing environment, the invention provides a cloud manufacturing system simulation method based on multiple intelligent agents, which is used for packaging various elements in the cloud manufacturing environment by applying a multi-intelligent agent technology, so that the characteristics of resources and services in the cloud manufacturing environment are fully embodied.
In a cloud manufacturing system, manufacturing resources are various, description and access modes of the manufacturing resources are more complex than those of computing resources in cloud computing, according to the characteristics of the resources and services in the cloud manufacturing system, the manufacturing resources are packaged and realized by using a simple intelligent body to form virtualized resources, the virtualized resources receive requests of other virtualized resources which are the same as the virtualized resources, a response is made according to rules, the response is generated according to the self state, the current state is reflected, historical data cannot be analyzed, and future trends cannot be predicted.
Preferably, the specific steps of obtaining the resource agent encapsulation model are as follows:
in a cloud manufacturing system, managing manufacturing resources by establishing a manufacturing resource pool;
the manufacturing resources are accessed to the manufacturing resource pool in a digital mode to form virtualized manufacturing resources, and a virtualized resource model is represented as:
RScmfg＝<RSID,Infostate,Templ,Data,Func01,Func02,...,Funcn>
wherein RSID is the unique identifier of the virtualized resource, InfostateIn the resource state, Templ is the resource template, Data is the manufacturing resource Data, FuncnIs a function of the virtualized resources.
Preferably, the resource templates are divided into static templates and dynamic templates.
In a cloud manufacturing system, a resource template is an important means for manufacturing resource virtualization, and can be divided into a static template and a dynamic template, which are described in a metadata manner, and each type of manufacturing resource has a unique resource template. The static template is used for recording basic description information of the manufacturing resources, and the information does not change or accumulate along with time; dynamic templates are used to record data or status data generated by manufacturing resources during the performance of a task, such as: real-time status data, maintenance data, tact data, and the like.
Preferably, the manufacturing resource data is divided into static data and dynamic data, the static data is recorded in the static template, and the dynamic data is recorded in the dynamic template.
In a cloud manufacturing system, manufacturing resources form manufacturing services through servicing, and the manufacturing services collect, extract, and process manufacturing resource data in order to provide corresponding services.
Preferably, the resource agent comprises a sensor, a condition-state rule, a processor and an executor, and when the sensor receives a request, the executor executes and responds according to the condition-state rule.
Preferably, the service modeling of the virtualized resources is to encapsulate the virtualized resources as manufacturing services, the cloud manufacturing system takes the services as a core, and the manufacturing services are realized by the service encapsulation of the virtualized resources.
In the cloud manufacturing system, the manufacturing service is realized by the following targets:
1. can be published publicly and can be called;
2. can be found, the service can be matched with the requirement through the service description;
3. can be combined through the service interface according to the demand.
According to the above objective, a service model is established as follows:
SEcmfg＝<SID,RSID,Infostate,Interface,InfoBasic,FuncTempl,FuncData,FuncOrder>
wherein SID is the unique identification of service, RSID is the unique identification of resource, InfostateFor state information, an Interface is an Interface for services.
Service agent modeling is the repackaging of manufacturing services to form a service agent. The resources in the cloud manufacturing form manufacturing services through service encapsulation, and in a simulation platform of the cloud manufacturing system, a service encapsulation method is the same as that in a service platform of the cloud manufacturing system.
Preferably, the service agent encapsulation model is expressed as follows under a cloud manufacturing simulation platform:
SAcmfg＝<SAID,SID,Infostate,Infobasic,MsgsA,clksA,Funcreq,Functrans,Funcquery,Funcrespond>
wherein SAID is the unique identification of the service agent, SID is the unique identification of the service, InfostateBeing state information, InfobasicFor serving basic information of agents, MagsAFor serving communication message controllers, Clks, between agentssAIs a clock serving an agent, FuncreqIssuing a function for demand, FunctransApplying a function for the transaction, FuncqueryFor active price-enquiring functions, FuncrespondAs a function of the passive transaction function.
Preferably, the service agent comprises a sensor, a state memory, a condition-state rule, a processor, a scheduler, and an actuator, wherein when the sensor receives an external request, the state changes, the external request is processed by the condition-state rule, the service agent schedules the relevant resource agent, and finally generates a response.
According to the technical scheme, the invention discloses and provides a cloud manufacturing system simulation method based on a service agent, and compared with the prior art, the cloud manufacturing system simulation method based on the service agent has the following beneficial effects:
1. the invention realizes packaging by utilizing the multi-agent technology aiming at the characteristics of elements such as resources, services and the like in the cloud manufacturing environment. And forming a resource intelligent agent, a service intelligent agent and a simulation framework, and realizing the simulation of the cloud manufacturing system by the method. The method integrates the characteristics of autonomy, independence, intelligence and the like of multiple intelligent agents, and the simulation authenticity is improved;
2. the invention provides the concrete encapsulation process and structure description of the resource agent, the service agent and the simulation framework, and the method is simple and easy to implement.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a diagram of a resource agent encapsulation model;
FIG. 2 is a diagram of a service agent encapsulation model;
FIG. 3 is a diagram of a multi-agent based cloud manufacturing simulation framework.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the invention discloses a cloud manufacturing system simulation method based on a service agent, and a cloud manufacturing simulation framework based on a plurality of agents is shown in figure 3. The framework comprises a service management module, a service agent and a resource agent. The method comprises the following concrete steps:
and performing virtual packaging on the manufacturing resources according to a Simple Reflex Agent standard to obtain a resource intelligent Agent packaging model.
As can be seen from FIG. 1, the resource agent includes a sensor, condition-state rules, a processor, and an executor, which executes and responds to the condition-state rules when the sensor receives a request.
Further, the specific steps of obtaining the resource agent encapsulation model are as follows:
in a cloud manufacturing system, managing manufacturing resources by establishing a manufacturing resource pool;
the manufacturing resources are accessed to the manufacturing resource pool in a digital mode to form virtualized manufacturing resources, and a virtualized resource model is represented as:
RScmfg＝<RSID,Infostate,Templ,Data,Func01,Func02,...,Funcn>
wherein the RSID is a unique identifier of the virtualized resource;
Infostatefor resource status, a virtualized resource may define different states to represent the real-time situation of the resource, the simplest being for example: idle, Busy, Suspend;
the Templ is a resource template, in a cloud manufacturing system, the resource template is an important means for manufacturing resource virtualization, and can be divided into a static template and a dynamic template, and is described in a metadata mode, and each type of manufacturing resource has a unique resource template. The static template is used for recording basic description information of the manufacturing resources, and the information does not change or accumulate along with time; dynamic templates are used to record data or status data generated by manufacturing resources during the performance of a task, such as: real-time status data, maintenance data, tact data, and the like;
data is manufacturing resource Data, is divided into static Data and dynamic Data as well as a resource template, and is recorded in the static template and the dynamic template respectively. In the cloud manufacturing system, manufacturing resources form manufacturing services through service, and the manufacturing services can acquire, extract and process manufacturing resource data in order to provide corresponding services;
Funcneach virtualized resource may be composed of a number of functions that can be service encapsulated to form a service for the function of the virtualized resource.
And packaging the virtualized resources into manufacturing services according to a Model-based Reflex Agent standard to obtain a service intelligent body packaging Model.
As can be seen from fig. 2, the service agent has a sensor, a state memory, condition-state rules, a processor, a scheduler, an executor. After the sensor receives the external request, the state changes, the state is processed through the condition-state rule, then the related resource intelligent bodies are scheduled, and finally the response is generated.
It should be noted that, the service agent modeling is divided into two steps, first, the virtualized resources are packaged into the manufacturing service; and secondly, the manufacturing service is encapsulated again to form a service agent.
The service modeling of the virtualized resources is to package the virtualized resources as manufacturing services, the cloud manufacturing system takes the services as a core, and the manufacturing services are realized by the service packaging of the virtualized resources.
In the cloud manufacturing system, the manufacturing service is realized by the following targets:
1. can be published publicly and can be called;
2. can be found, the service can be matched with the requirement through the service description;
3. can be combined through the service interface according to the demand.
According to the above objective, a service model is established as follows:
SEcmfg＝<SID,RSID,Infostate,Interface,InfoBasic,FuncTempl,FuncData,FuncOrder>
wherein the SID is a unique identification of the service for determining a specific service in the environment;
the RSID is a unique identifier of the resource, and the service and the resource are in a many-to-many relationship, that is: encapsulating a resource into a service; one resource may form a plurality of services; a plurality of resources cooperate to form a service. Thus, in this embodiment, the RSID represents an ID of a resource or an ID of a group of resources;
Infostatethe service state change is represented as follows:
Infostate＝{Check,Publish,Idle,Busy,Unavailable}
the Check state refers to a process that a service has an audit after being released, the process determines the reasonability and feasibility of the service by a manager, and in the process, the service is in a state to be audited, and the service is unavailable at the moment;
publish is when the administrator determines that the service can be called after the service is audited, and the service is in an open state but is not available;
idle is an Idle state of a service, which is in its current state when the service provider determines that the service is ready and can be invoked after the service has been audited and publicly released. In addition, when the service completes one call and is ready for the next work, the service is in the current state, and the service is available at the moment;
busy is a Busy state of a service, and means that when the service is performing a job and cannot accept other jobs at the same time, the service is in a current state, and the service is unavailable;
the Unavailable is a state that the service is Unavailable, and the state refers to that the service is temporarily Unavailable to be called due to some reason or service maintenance after the service is audited and published publicly, and the service is Unavailable at the moment;
the Interface is an Interface of a service, is an important component of the service, and is an important condition for constructing a service network. Whether two services can be combined or not is judged by the definition of the interface, regardless of the service call, the service combination and the service network. In the service call, whether the input item of the service can meet the requirement of service execution and whether the output result of the service can be used are also judged through the service interface.
Further, service agent modeling is to encapsulate the manufacturing service again to form a service agent encapsulation model. In the cloud manufacturing, the resources form manufacturing services through service encapsulation, and in the simulation platform of the cloud manufacturing system, the method of the service encapsulation is the same as that in the service platform of the cloud manufacturing system. The method of servicing is the same regardless of the actual manufacturing resources or the virtualized resources provided by the simulation platform.
The service agent in the cloud manufacturing system can be a service provider and a service user, so that the service agent has the characteristics of both the provider and the user. Two roles and four behaviors are included, and the two roles are: the service provider and the service user, and the four actions are:
1. when the service provider is used as a service user, the service user can issue a demand signal, wait for the service provider to respond, and further select the service provider according to the rule to carry out information interaction.
2. When the service provider is a service provider, an application signal is issued, and the service provider receives a request signal issued by a service user in a bulletin board, and issues the application signal when the condition is satisfied, and cooperates with the service user when the service user receives the application signal.
3. When the service user is served, the service user actively issues a demand signal, the service user actively searches for the service provider, bargaining is started after the service provider is idle and responds, and finally cooperation is carried out under the condition that the service provider and the service provider agree.
4. When the service provider is used as a service provider, the transaction signal is passively received, when the service user actively finds the service provider, the service provider responds according to the current state, and finally, cooperation is carried out under the condition that the two parties agree.
These four basic behaviors can be combined and modified in rules.
The service intelligent agent model under the cloud manufacturing simulation platform is expressed as follows:
SAcmfg＝<SAID,SID,Infostate,Infobasic,MsgsA,clksA,Funcreq,Functrans,Funcquery,Funcrespond>
wherein the SAID is a unique identifier of the service agent for determining a specific service agent in the environment;
SID is the only identification of service, a service agent encapsulates a service, and the identification is used for determining the specific service encapsulated by the current service agent;
Infostatethe state information is used for describing dynamic information of the service agent in different roles, wherein the dynamic information comprises four kinds of state information, and the four states respectively correspond to feedback of four functions;
Infobasicfor serving agentsBasic information for storing some basic description, rules and data;
MagsAto serve a communication message controller between agents,
MsgsA＝<ps,pe,Queuemsg＞
the messages in the model are represented in the form of message queues. The system message queue stores all messages in the system according to time, and the message controller in the service agent is in the service agent clock ClksAMigrating the message of the current service agent in the queue to an independent message queue of the current service agent under the trigger of pe and ps, wherein pe and ps are pointers of the system message queue and are used for recording the start-stop position of the last message in the system message. QueuemsgThe method comprises the steps that a message queue of a service intelligent agent records the message of the current service intelligent agent;
ClksAthe clocks of the service agents are different in response frequency from one service agent to another. Each time the clock is triggered, the function Func is activated once. Thus, the clock also represents the speed of reaction of the currently serving agent. In the simulation process, the execution speed of an enterprise, the updating speed of service or the running capacity of a virtual machine can be reflected;
Funcreqissuing a function for the demand, the function being triggered when the service agent acts as a service user;
Functransapplying a function for the transaction, the function being triggered when the service agent acts as a service provider;
Funcquerythe function is an active price inquiring function, and the function is triggered when the service agent is used as a service user role;
Funcrespondas a function of the passive transaction function. This function is triggered when the service agent acts as a service provider.
And defining a communication interface and a communication mode on the basis of the resource intelligent body packaging model and the service intelligent body packaging model.
And establishing a cloud manufacturing simulation framework based on the multi-agent based on the resource agent packaging model and the service agent packaging model.
As can be seen from fig. 3, the framework includes a service management module, a service agent, and a resource agent. The service agents obtain service information or tasks through communication with the service management module, and meanwhile, other service agents interact and cooperate. And scheduling the related resource agents after the task is determined. And after receiving the task, the resource intelligent agent interacts and cooperates with other related resource intelligent agents to finally complete the task and feed back the task.
In the implementation case of a typical smart manufacturing resource 3D printer, modeling will be done in a bottom-up fashion for such manufacturing resources. First, a static template of the resource is built, describing the modules to be collected or controlled in the manufacturing resource in the form of meta-templates. In this case, the modules of the head, the material cartridge, the energy consumption sensor, the temperature sensor, and the like are described. The specific parameters described include control interfaces, control protocols, transmission rates, etc., among others. Next, a dynamic template of the manufacturing resource is constructed for the collected information of the resource, such as real-time temperature and real-time energy consumption. The two types of templates have different sampling time, so that the two types of templates are divided into two types of dynamic templates in design and a time module is sampled. Resource _01 is static data, and Resource _02 and Resource _03 are dynamic data, which are stored in a dynamic database and a static database of the Resource, respectively. Thus, the resource model has been built. For such resources, a reference service of the template can be provided in the service process, namely the acquisition of the template structure; data extraction service, namely acquisition of dynamic and static data; in addition, for the open control port, the control service of the manufacturing resource can be realized.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (8)
1. A cloud manufacturing system simulation method based on a service agent is characterized by comprising the following steps:
performing virtual packaging on the manufacturing resources to form virtual resources, and simultaneously obtaining a resource intelligent body packaging model;
packaging the virtualized resources into manufacturing service to obtain a manufacturing service model;
packaging the manufacturing service again to obtain a service agent packaging model;
defining a communication interface and a communication mode on the basis of the resource agent encapsulation model and the service agent encapsulation model;
and establishing a cloud manufacturing simulation framework based on the multi-agent based on the resource agent packaging model and the service agent packaging model.
2. The cloud manufacturing system simulation method based on the service agent as claimed in claim 1, wherein the specific steps of obtaining the resource agent encapsulation model are as follows:
in a cloud manufacturing system, managing manufacturing resources by establishing a manufacturing resource pool;
the manufacturing resources are accessed to the manufacturing resource pool in a digital mode to form virtualized manufacturing resources, and a virtualized resource model is represented as:
RScmfg＝<RSID,Infostate,Templ,Data,Func01,Func02,...,Funcn>
wherein RSID is the unique identifier of the virtualized resource, InfostateIn the resource state, Templ is the resource template, Data is the manufacturing resource Data, FuncnIs a function of the virtualized resources.
3. The service agent-based cloud manufacturing system simulation method of claim 2, wherein the resource templates are divided into static templates and dynamic templates.
4. The cloud manufacturing system simulation method based on service agents as claimed in claim 3, wherein the manufacturing resource data is divided into static data and dynamic data, the static data is recorded in the static template, and the dynamic data is recorded in the dynamic template.
5. The service agent-based cloud manufacturing system simulation method of claim 1, wherein said resource agent encapsulation model comprises sensors, condition-state rules, processors and executors.
6. The service agent-based cloud manufacturing system simulation method of claim 1, wherein the manufacturing service model is expressed as:
SEcmfg＝<SID,RSID,Infostate,Interface,InfoBasic,FuncTempl,FuncData,FuncOrder>
wherein SID is the unique identification of service, RSID is the unique identification of resource, InfostateFor state information, an Interface is an Interface for services.
7. The service agent-based cloud manufacturing system simulation method according to claim 1, wherein the service agent encapsulation model is expressed as:
SAcmfg＝<SAID,SID,Infostate,Infobasic,MsgsA,clksA,Funcreq,Functrans,Funcquery,Funcrespond>
wherein SAID is the unique identification of the service agent, SID is the unique identification of the service, InfostateBeing state information, InfobasicFor serving basic information of agents, MagsAFor serving communication message controllers, Clks, between agentssAIs a clock serving an agent, FuncreqIssuing a function for demand, FunctransApplying a function for the transaction, FuncqueryFor active price-enquiring functions, FuncrespondAs a function of the passive transaction function.
8. The service agent-based cloud manufacturing system simulation method of claim 1, wherein the service agent encapsulation model comprises sensors, state memory, condition-state rules, processors, schedulers, and executors.
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| CN113283785A (en) * | 2021-06-09 | 2021-08-20 | 广东工业大学 | Cooperative scheduling optimization method for multi-task manufacturing resources |
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